An improved genetic algorithm for degree constrained minimum spanning trees

The Minimum Spanning Tree (MST) is of crucial importance for Communication Networks (CNs), which can solve problems of unconstrained CNs effectively. However, in practical CNs, the degree of the spanning tree is constrained. In such a case, the problem is very difficult, which has been proved to be NP-hard. In this paper, an improved genetic algorithm (I-GA) is proposed for solving the problem of Degree Constrained Minimum Spanning Tree (DCMST). We use Prufer number as the chromosome, and improve the crossover and mutation processes of the existing genetic algorithm for obtaining high locality, heritability, and self-adaptation. Simulation results show that our mechanism of I-GA can get relatively better results.